Muscular co-contraction is related to varus thrust in patients with knee osteoarthritis
Bibliographic record
Abstract
BACKGROUND: Patients with knee osteoarthritis often present with varus thrust and muscular co-contraction during gait. It is unclear if these adaptations are related. The objective was to examine the relationship between muscle co-contraction and varus thrust during gait in patients with knee osteoarthritis and to determine if these relationships are modulated by disease severity or history of knee ligament rupture. METHODS: Participants (n = 42, 23 women, mean age 58 years) with knee osteoarthritis completed gait trials at self-selected speeds. Varus thrust was measured with an eight camera motion capture system sampled at 100 Hz. Co-contraction ratios were measured with surface electromyography sampled at 2000 Hz over the quadriceps, hamstrings, and gastrocnemius. Disease severity was measured on radiographs and history of anterior cruciate ligament rupture was confirmed on magnetic resonance imaging. Linear regression analyses examined the relationship between varus thrust and co-contraction ratios after controlling for radiographic disease severity and history of anterior cruciate ligament rupture. FINDINGS: = 0.168) co-contraction ratios were associated with greater varus thrust. Quadriceps-gastrocnemius co-contractions ratios were not related to varus thrust (P > 0.05). Radiographic disease severity or history of anterior cruciate ligament injury did not significantly contribute to regression models. INTERPRETATION: Greater quadriceps-hamstring co-contraction is associated with greater varus thrust in patients with knee osteoarthritis. Potential explanations include increased co-contraction may provide stability or there is a proprioceptive reflex that is independent of any stabilizing role. Research is needed to test these hypotheses.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".